Introduction

The objective of this analysis is to cluster players in the NBA by their “true position” rather than the traditional PG/SG/SF/PF/C. The modern NBA has become “positionless” and players have been designated specific “roles” on the squad based on their performance. For example, Some athletic centers can now play point guard or in some cases an offense is designed around a specific player. We will seek to find what those “true positions” or clusters are and do some learning as to how those positions look like on different rosters. The key questions we hope to answer are the following:

  1. What player types or “true positions” exist in the NBA and skills do they encompass?
  2. How are winning teams constructed with these “true positions”?
  3. Where on the floor are these clusters more efficient in terms of shooting?
  4. How do these players effect "Win Probability intra-game?
  5. How do we value these “true positions” in the NBA?

All of these questions, we will be comparing the Portland Trail Blazers to other teams in the NBA. Portland has a long standing history of making the playoffs. Since the inception of the franchise in 1970, the organization has made the playoffs 37 times including a 21 straight appearance streak from 1983 to 2003. Since 2010-11 season, The Portland Trail Blazers only missed the playoffs during the 2011-12 & 2012-13 season. They currently only the league’s longest consecutive playoff streak. Given all of that, other teams have eclipsed the Blazers in terms of championship success. The Blazers only conference titles were in 1977, 1990, and 1992. We will be examining where some of the shortcomings may have come from as a way to compare the Blazers to other comparable teams.

To identify “true positions”, we will first do a Principle Components Analysis from 36 variables that encompass a lot of common player statistics such as shooting (FG %, 3P %, etc), Assists, Steals, Blocks, Rebounding, and a number of efficiency metrics (VORP, EFG %). All of these stats are per game statistics. In order to prep the statistics, we need to “scale” the variables as to transform the variables to be all on the same scale. This is important so that not one variable is weighted more than the other just given that it would have a higher overall number. A Principle Components Analysis looks for variables that are highly correlated with each other and combines them into a new variable. This analysis will reduce the 36 variables to a few, highly correlated variables. This is helpful to identify clusters of “skillsets”. We can see the PCA Plot below how some of the variables start to cluster together.

The “Scree Plot” is a useful visualization to show how much variance is explained in each newly constructed “PCA” variables. We can see the 1st dimension combined 37% of the variables into 1 dimension, the 2nd dimension is comprised of the 21.8% of the variables and so on. For our analysis, we will be using the first 6 dimensions as that encompasses 83.1% of the original variables. This is a sufficiently high percentage for us.

The following 6 charts help to explain what each of those newly constructed PCA variables are comprised of from the original variables. Our first (37.3% variance explained) is made up of “Scoring” variables. The 2nd (21.8% variance explained) is made up of “Rebounding” variables. As we notice from the “Scree Plot” from here the variables start to drop off in secondary variables and loose formations from the original variables. Our 3rd variable is comprised of Effective Field Goal Percentage (EFG %) and True Shooting Pct % (TSPercent). Our 4th variable is made up of “Defensive” metrics of Defensive Box Plus/Minus (DBPM) and “Steal Percentage”. The 5th and 6th variables are very specific with the 5th only really accounting for Free Throw Rate and the 6th being just Turnover Over Percent (TOV%) or Ball Handling. The combined variables can be thought of a “skillset” comprised of each true position.

With our variables cleaned up and combined, we will now perform a K-means cluster analysis, a form of Unsupervised Machine Learning to reduce the rows of data into grouped clusters. This will help us identify how many “true positions” exist amongst all the players statistics. Essentially, the K-means iterates through to figure out the average of all PCA variables and helps to assign a cluster variable to players with similar average values across all inputted variables. In order to determine how many clusters exist, we can several different methods. We will be using a Sum of Square method to identify appropriate number of clusters amongst the data points. The goal of this percentage is to to say how much total variance of the data set can be explained by clustering. The overall goal of K-means is to minimize the within group dispersion and maximize the between-group dispersion. More simply put, it’s better to find a few broad clusters that can encompass many players than very specific clusters that would over-generalize their group fit.

The table below shows that at 7 clusters, we can account for a majority of the variance at 52% of the dataset. This figure is without the inputted PCA variables. 52% is a low enough number to account for the generality. These numbers also tell us that there a lot of players with very specific player profiles.

Cluster K Between SS Percentage % (Non-PCA)
k between_ss_per
3 0.3628221
4 0.4322870
5 0.4735695
6 0.5017592
7 0.5217006
8 0.5397135
9 0.5528497
10 0.5664978

This chart below shows the overlapping of some of the 7 clusters in overall similarity. If we had a higher “K” cluster, we would have more overlap.

Next, we input our K-means with our newly constructed PCA variables. As we can see, we get a 61% Sum of Square Percentage at 7 clusters, which tells us that the indiviudal statistics were causing too much variation. By combining some highly correlated statitics, we were able to reduce overall variance.

Cluster K Between SS Percentage (PCA Variables) %
k between_ss_per
3 0.4329150
4 0.5114912
5 0.5596262
6 0.5804838
7 0.6133119
8 0.6336246
9 0.6487817
10 0.6597330

We still have some overall overlap with the PCA variables inputted but that may be expected.

With 7 clusters determined from our dataset, we’ve renamed the clusters with more common names that we can interpret from. The following table shows how the PCA variables align in terms cluster fits. More simply put, what skillsets each “true positions” are made up off. In terms of the 7 clusters, we have identified the following names from the clusters: “Superstars”, “Scoring Big Men”, “Perimeter Wing/Defenders”, “Floor Generals”, “Defensive Big Men”, “Perimeter Shooter” and “Role Players”. “Superstars” are your all-around players and have the highest value on the team in terms of scoring, some defense, and shooting efficiency. They lack in terms of rebounding and defense, which the Scoring Big Men are better at. These are the primary “All-stars” on the roster. Perimeter Wings/Defenders are your secondary superstar scorers and have an all-around game. Defense Big Men are secondary Scoring Big Man with more of a focus on defense and rebounding. Floor Generals are efficient scorers, passers and ball handling. They likely don’t show up too much in the box score. Perimeter Shooters are your sparks off the bench but are one-way offense backups and don’t really provide much value in terms of defense. Lastly, Role Players are your scrubs and rotation players that don’t have much value all around in terms of game statistics. The PCA averages can be a bit difficult to interpret but for “Rebounding” and “Shooting Efficiency”, the highest value is negative. For the other variables, the higher the positive value the more that player in the cluster is better at that specific variable.

VORP = Value over replacement player (Box score estimate of estimate points per 100 team possessions that a player contributes over a replacement or average player during that time frame); Kobe Bryant averaged around a 8 in VORP, Lebron James averages a 9 VORP, Michael Jordan averaged a 10 in VORP. Those are top-end numbers.

PCA Value Avgs. Per Cluster
Cluster Player_Count VORP Scoring Rebounding ShootingEff Defense FreeThrows BallHandling
Superstar 353 3.46 6.36 3.16 0.57 -0.56 -0.71 -0.54
Scoring Big Man 371 2.24 5.39 -3.71 0.74 0.87 0.41 -0.15
Perimeter Wing/Defender 636 1.08 1.38 1.26 -1.04 0.77 0.75 0.19
Floor General 575 0.60 0.17 2.08 1.29 -0.79 -0.30 0.57
Defensive Big Man 586 0.37 -0.47 -4.15 -0.04 -0.36 -0.49 0.12
Perimeter Shooter 835 0.30 -2.36 0.58 -1.44 -0.13 0.14 -0.18
Role Player 710 -0.27 -4.28 0.28 1.44 0.23 -0.05 -0.35
a Rebounding/ShootingEff is the only value where a negative value is highest

Trail Blazers Analysis

Now that we have our clusters built and assigned it’s now time to look at how the Trail Blazers roster has been constructed.

In order to do so, we need to establish some context in terms of team’s performance. 2018 was likely the biggest underachieving year given they were a 3rd seed and had a first round exit. 2019 was the best final result in a Western Conference Final appearance (CF stands out Conference Final exit). 2020 & 2021 featured two first round exits for the Blazers. The 2019 is likely considered the best team constructed for the Blazers. We will dive into why the team fell so much in terms of performance after the 2019 season.

Portland Trail Blazers Playoff Results by Year
Year Team Seed Result
2010 POR 6 FR
2011 POR 6 FR
2014 POR 5 SEMI
2015 POR 4 FR
2016 POR 5 SEMI
2017 POR 8 FR
2018 POR 3 FR
2019 POR 3 CF
2020 POR 8 FR
2021 POR 6 FR
a FR = First Round
b SEMI = 2nd round exit
c CF = Conference Finals exit

Now that we have an understanding of the clusters in our dataset, it’s important to now understand how Portland’s roster has been constructed in relation to other Playoff & Championship teams. As we saw earlier we saw earlier Scoring Big Men aren’t too far off from Superstars in terms of value added to the roster.

The two charts below show % of Superstars & Scoring Big Men on each roster since 2010. Every Championship team since 2010 has had at least 2 Superstars or Scoring Big Man (or combination of the two) on the team with the exception of 2014 & 2011 teams. Superstars are good on all facets of their games. They are excellent at scoring, defense and elevating others. The difference between them and Scoring Big Men are that Scoring Big Men are better rebounders. If we breakdown the last 10 champions, here are notable players from their roster in terms of being either a Scoring Big Man or Superstar.

2021 MIL: Middleton (Superstar), Holiday (Superstar), Antetokounmpo (Scoring Big Man)

2020 LAL: James (Superstar), Davis (Scoring Big Man)

2019 TOR: Leonard (Superstar), Lowry (Superstar), Siakam (Scoring Big Man), Valanciunas (Scoring Big Man), Ibaka (Scoring Big Man)

2018 GSW: Curry (Superstar), Durant (Superstar), Green (Scoring Big Man)

2017 GSW: Curry (Superstar), Durant (Superstar), Green (Scoring Big Man)

2016 CLE: James (Superstar), Irving (Superstar), Love (Scoring Big Man)

2015 GSW: Curry (Superstar), Thompson (Superstar), Green (Scoring Big Man)

2014 SAS: Duncan (Scoring Big Man)

2013 MIA: James (Superstar), Wade (Superstar), Bosh (Scoring Big Man)

2012 MIA: James (Superstar), Wade (Superstar), Bosh (Scoring Big Man)

2011 DAL: Nowitzki (Superstar)

2010 LAL: Bryant (Superstar), Gasol (Scoring Big Man), Odom (Scoring Big Man), Bynum (Scoring Big Man)

In terms of roster, the Blazers have looked like the following over the years:

2021 POR: Lillard (Superstar), Nurkic (Scoring Big Man), Kanter (Scoring Big Man)

2020 POR: Lillard (Superstar), Whiteside (Scoring Big Man)

2019 POR: Lillard (Superstar), Nurkic (Scoring Big Man)

2018 POR: Lillard (Superstar), Nurkic (Scoring Big Man)

2017 POR: Lillard (Superstar), McCollum (Superstar), Plumlee (Scoring Big Man)

2016 POR: Lillard (Superstar), McCollum (Superstar), Plumlee (Scoring Big Man)

2015 POR: Lillard (Superstar), Aldridge (Scoring Big Man)

2014 POR: Lillard (Superstar), Aldridge (Scoring Big Man), Lopez (Scoring Big Man)

2013 POR: Lillard (Superstar), Aldridge (Scoring Big Man), Hickson (Scoring Big Man)

2012 POR: Aldridge (Scoring Big Man)

2011 POR: Aldridge (Scoring Big Man)

2010 POR: Roy (Superstar), Aldridge (Scoring Big Man)

Here are a couple notes regarding Portland’s roster: CJ McCollum hasn’t been playing at Superstar level since 2017. Damian Lillard has been the only Superstar on the roster since compared to other Championship Level teams. In terms of player Archetype, players have stepped up (sort of) to be that potential sidekick with Damian Lillard but as you can see the person is diferent from year to year. One interesting question here is if McCollum’s game was stifled by the addition to Nurkic to the roster.

Put simply, Portland has been at its best when its had more Perimeter Shooters on the roster. We can see for 2020 & 2021, there wasn’t as much perimeter shooters, which left Damian Lillard/CJ McCollum having to shoulder the load of shooting. Instead the Blazers shifted in roster strategy to opt for more all-around perimeter defenders vs. the fully offensive perimeter shooters. I’m not saying to sacrifice defense but getting players on the roster who are more defensive players didn’t work well for the 2020 & 2021 Blazers. The Perimeter Shooters on the Blazers in team in 2018 & 2019 were Seth Curry (2019), Jake Layman (2019), Meyers Leonard (2018/19), Pat Connaughton (2018), Maurice Harkless (2018) and Evan Turner (2018). The only shooters left on the team for 2020/2021 were Anfernee Simons, Gary Trent Jr. (traded in 2021) and Nassir Little (only for 2021). It may be wise for the Blazers to sign a dedicated Perimeter Shooter to jolt the secondary offense as Seth Curry would have for the Blazers in the past. Another concern for the Blazers, is the high % of “Role Players” on the roster compared to other playoff teams in 2020/21. This is due solely to low performance. The 2020 squad had a high % of Role Players in Kent Bazemore, Mario Hezonja, Nassir Little, and Anthony Tolliver. In short, most of the players were purely bad signing for the Blazers. Not surprisingly, the 2019 roster had no “Role Players” as the entire roster had an elevated role with the team. The 2018 role players were Zach Collins and Jake Layman who both developed out of those roles in the 2019 season. It’s not uncommon to see young players designated as “Role Players” (i.e. Zach Collins/Jake Layman) but having veterans with the role player designation is just wasted roster capital.

Shooting Tendencies by Cluster

Next we want to look at where on the court different clusters end up shooting effiently from. Obviously, this could change from team to team but know a team’s deficiencies and what player types excel in those deficiencies could improve an offense.

Portland usually shoots at a higher level on left/right wing compared to other playoff teams. We can attribute the Wing performance to Dame & CJ’s shooting zone. Portland lacks in shooting in the Paint and the Corners compared to other Playoff teams dating back to 2016. Given the change of “Scoring Big Man” YoY, we attribute the volatilty in the paint due to reliability of a scoring big man to play alongside Dame/CJ. What’s interesting is the improvement of the Paint FG % amongst Playoff teams over time. The 2020 squad was the best shooting in team in the past 6 seasons for the Blazers albeit a short season.

Link to shooting zones: https://thevi5ion.wordpress.com/2019/03/10/college-basketball-shot-chart-tool/

FG Pct by Shooting Zone
Team Year Paint Left Corner Right Corner Left Wing Right Wing Left Baseline Right Baseline Left Elbow Right Elbow
Portland
POR 2016 0.39 0.35 0.39 0.37 0.37 0.36 0.41 0.39 0.42
POR 2017 0.44 0.38 0.36 0.34 0.36 0.40 0.42 0.40 0.42
POR 2018 0.50 0.39 0.40 0.37 0.36 0.44 0.45 0.37 0.40
POR 2019 0.51 0.36 0.36 0.36 0.38 0.42 0.42 0.40 0.41
POR 2020 0.53 0.44 0.41 0.35 0.38 0.43 0.41 0.42 0.40
POR 2021 0.51 0.36 0.40 0.40 0.39 0.41 0.45 0.41 0.41
Playoff Teams
Playoff 2016 0.45 0.38 0.36 0.34 0.34 0.39 0.40 0.38 0.39
Playoff 2017 0.48 0.39 0.39 0.36 0.35 0.40 0.40 0.39 0.39
Playoff 2018 0.56 0.40 0.39 0.36 0.35 0.41 0.40 0.40 0.40
Playoff 2019 0.55 0.39 0.38 0.35 0.35 0.42 0.40 0.40 0.40
Playoff 2020 0.55 0.39 0.39 0.35 0.36 0.41 0.41 0.41 0.40
Playoff 2021 0.55 0.40 0.41 0.37 0.37 0.42 0.42 0.41 0.41
Finals Teams
Finals 2016 0.46 0.42 0.40 0.40 0.37 0.41 0.41 0.40 0.41
Finals 2017 0.49 0.39 0.47 0.38 0.38 0.44 0.44 0.40 0.41
Finals 2018 0.61 0.39 0.40 0.37 0.36 0.45 0.41 0.45 0.43
Finals 2019 0.58 0.43 0.41 0.37 0.35 0.44 0.46 0.44 0.42
Finals 2020 0.59 0.36 0.40 0.35 0.35 0.36 0.38 0.39 0.40
Finals 2021 0.60 0.40 0.43 0.37 0.35 0.43 0.40 0.43 0.43
Championship Teams
Champs 2016 0.42 0.35 0.37 0.34 0.34 0.40 0.41 0.37 0.39
Champs 2017 0.52 0.41 0.48 0.38 0.40 0.44 0.45 0.39 0.44
Champs 2018 0.61 0.40 0.41 0.37 0.36 0.47 0.42 0.48 0.46
Champs 2019 0.56 0.42 0.38 0.35 0.34 0.39 0.47 0.43 0.41
Champs 2020 0.60 0.37 0.41 0.34 0.32 0.34 0.40 0.38 0.37
Champs 2021 0.60 0.40 0.43 0.37 0.35 0.43 0.40 0.43 0.43

When looking at specific Player cluster shooting performance by Shooting Zone, we can see that Perimeter Shooters are more likely to score higher in the paint. This could be their nature to be both spot up shooters and screening to an open layup given their movement on the floor. The Blazers’ Perimeter Wings/Defenders are less efficient in the Paint compared to other playoff team, which may be why more playoff teams have a higher percentage of Perimeter Shooters on the roster. One other interesting insight is that the Blazers’ Big Man (Scoring/Defensive) have been less efficient in the paint compared to other playoff teams.

Cluster FG Pct by Shooting Zone
Cluster Paint Left Corner Right Corner Left Wing Right Wing Left Baseline Right Baseline Left Elbow Right Elbow
Portland
Defensive Big Man 0.52 0.25 0.36 0.29 0.29 0.30 0.31 0.32 0.36
Floor Generals 0.45 0.41 0.23 0.27 0.39 0.42 0.41 0.40 0.40
Perimeter Shooter 0.52 0.37 0.44 0.36 0.39 0.40 0.42 0.41 0.42
Perimeter Wings/Defenders 0.46 0.42 0.38 0.38 0.37 0.45 0.43 0.40 0.42
Role Player 0.44 0.32 0.35 0.30 0.33 0.29 0.31 0.28 0.32
Scoring Big Man 0.52 0.00 0.00 0.25 0.19 0.34 0.42 0.33 0.37
Superstars 0.47 0.37 0.39 0.39 0.38 0.41 0.45 0.42 0.42
Playoff Teams
Defensive Big Man 0.57 0.34 0.33 0.33 0.31 0.40 0.40 0.39 0.39
Floor Generals 0.48 0.39 0.38 0.35 0.34 0.38 0.40 0.38 0.38
Perimeter Shooter 0.52 0.40 0.39 0.36 0.36 0.41 0.39 0.39 0.38
Perimeter Wings/Defenders 0.53 0.41 0.40 0.36 0.36 0.42 0.40 0.40 0.40
Role Player 0.45 0.34 0.34 0.30 0.30 0.38 0.34 0.35 0.35
Scoring Big Man 0.57 0.34 0.35 0.33 0.32 0.39 0.40 0.40 0.40
Superstars 0.53 0.40 0.41 0.36 0.36 0.43 0.42 0.41 0.42

In comparing the Perimeter Shooters to Wing/Defenders over time, we can generally see that Perimeter Shooters have been higher performing across each zone compared to Wing/Defenders. The exception mainly being the 2020 season where the Blazers were a better shooting team overall (shortened season could be a reason why).

Portland Perimeter Clusters FG Pct by Shooting Zone by Year
Cluster season Paint Left Corner Right Corner Left Wing Right Wing Left Baseline Right Baseline Left Elbow Right Elbow
Perimeter Wings/Defenders
Perimeter Wings/Defenders 2016 0.35 0.40 0.39 0.35 0.33 0.40 0.41 0.35 0.39
Perimeter Wings/Defenders 2017 0.40 0.34 0.28 0.35 0.26 0.30 0.41 0.38 0.40
Perimeter Wings/Defenders 2018 0.47 0.48 0.42 0.37 0.36 0.43 0.45 0.38 0.40
Perimeter Wings/Defenders 2019 0.48 0.39 0.37 0.34 0.39 0.46 0.46 0.39 0.45
Perimeter Wings/Defenders 2020 0.50 0.57 0.43 0.34 0.36 0.46 0.41 0.43 0.43
Perimeter Wings/Defenders 2021 0.46 0.39 0.40 0.42 0.39 0.46 0.44 0.42 0.40
Perimeter Shooter
Perimeter Shooter 2016 0.50 0.35 0.49 0.36 0.33 0.37 0.43 0.43 0.45
Perimeter Shooter 2017 0.48 0.39 0.41 0.29 0.40 0.48 0.40 0.36 0.42
Perimeter Shooter 2018 0.55 0.32 0.40 0.38 0.39 0.41 0.50 0.44 0.41
Perimeter Shooter 2019 0.60 0.38 0.41 0.40 0.41 0.41 0.32 0.39 0.41
Perimeter Shooter 2020 0.43 0.40 0.46 0.31 0.39 0.33 0.39 0.45 0.43
Perimeter Shooter 2021 0.48 0.51 0.50 0.39 0.40 0.57 0.43 0.41 0.31

One interesting observation when comparing Dame/CJ is that CJ is better in Dame is shooting from any spot on the floor whereas Dame tend to be pretty spotty. It could be that CJ’s had to transform his game to complement Dame, which is why he’s more versatile shooting on any part of the floor. What’s also interesting that although CJ is no longer categorized as a Superstar, it may be due to the fact that his offensive game and shooting efficiency has taken off rather than other parts of his game have suffered as a result.

Dame/CJ FG Pct by Shooting Zone by Year
Player season Cluster Shots Paint Left Corner Right Corner Left Wing Right Wing Left Baseline Right Baseline Left Elbow Right Elbow
2016
CJ McCollum 2016 Superstars 1441 0.39 0.41 0.32 0.39 0.45 0.40 0.44 0.40 0.47
Damian Lillard 2016 Superstars 1445 0.36 0.33 0.44 0.36 0.37 0.33 0.37 0.38 0.39
2017
CJ McCollum 2017 Superstars 1407 0.46 0.34 0.48 0.40 0.43 0.42 0.44 0.47 0.47
Damian Lillard 2017 Superstars 1388 0.45 0.60 0.48 0.34 0.34 0.45 0.39 0.45 0.37
2018
CJ McCollum 2018 Perimeter Wings/Defenders 1523 0.47 0.41 0.37 0.41 0.39 0.46 0.48 0.37 0.44
Damian Lillard 2018 Superstars 1433 0.50 0.32 0.36 0.42 0.34 0.64 0.52 0.33 0.38
2019
CJ McCollum 2019 Perimeter Wings/Defenders 1525 0.48 0.34 0.47 0.38 0.40 0.47 0.47 0.40 0.47
Damian Lillard 2019 Superstars 1743 0.48 0.31 0.48 0.38 0.37 0.44 0.47 0.43 0.41
2020
CJ McCollum 2020 Perimeter Wings/Defenders 1408 0.50 0.57 0.50 0.34 0.36 0.51 0.43 0.44 0.48
Damian Lillard 2020 Superstars 1322 0.53 0.55 0.33 0.40 0.40 0.31 0.49 0.45 0.33
2021
CJ McCollum 2021 Perimeter Wings/Defenders 1000 0.50 0.36 0.35 0.40 0.42 0.55 0.39 0.42 0.50
Damian Lillard 2021 Superstars 1388 0.54 0.17 0.27 0.41 0.41 0.26 0.55 0.42 0.46
a Filtered for Dame/CJ

One area of development for Anfernee Simons is hit shooting efficiency in the paint. Other Perimeter Shooters such as Jake Layman, Pat Connaughton, Seth Curry were good spot up shooters like Anfernee but way more efficient in the paint. It could be good to develop Anfernee’s pump fake drive to the hoop game that we’ve come to see with CJ McCollum’s game. Another interesting trend here is around Portland’s decision to trade away Gary Trent Jr, he somewhat regressed in terms of FG % in his 2nd year. Although he had success with the Raptors, he was not positioned well in the Blazers offense. One concern is Nassir Little, who we’d expect to regress to a Role Player if his offensive game doesn’t expand.

Perimeter FG Pct by Shooting Zone by Year
Player season Cluster Shots Paint Left Corner Right Corner Left Wing Right Wing Left Baseline Right Baseline Left Elbow Right Elbow
2016
Allen Crabbe 2016 Perimeter Shooter 670 0.56 0.42 0.47 0.35 0.35 0.35 0.42 0.45 0.47
Al-Farouq Aminu 2016 Perimeter Wings/Defenders 636 0.35 0.40 0.39 0.35 0.33 0.40 0.41 0.35 0.39
Gerald Henderson 2016 Perimeter Shooter 455 0.46 0.32 0.54 0.24 0.27 0.36 0.38 0.38 0.38
Meyers Leonard 2016 Perimeter Shooter 427 0.49 0.17 0.50 0.45 0.33 0.43 0.56 0.44 0.48
2017
Allen Crabbe 2017 Perimeter Shooter 619 0.48 0.37 0.38 0.27 0.46 0.80 0.34 0.38 0.47
Maurice Harkless 2017 Perimeter Wings/Defenders 432 0.41 0.23 0.23 0.38 0.34 0.50 0.57 0.41 0.43
Al-Farouq Aminu 2017 Perimeter Wings/Defenders 411 0.40 0.43 0.33 0.33 0.18 0.17 0.30 0.36 0.38
Meyers Leonard 2017 Perimeter Shooter 362 0.45 0.44 0.46 0.31 0.28 0.11 0.50 0.35 0.39
Pat Connaughton 2017 Perimeter Shooter 78 0.52 0.33 0.67 0.38 0.50 0.50 0.00 0.25 0.14
2018
CJ McCollum 2018 Perimeter Wings/Defenders 1523 0.47 0.41 0.37 0.41 0.39 0.46 0.48 0.37 0.44
Evan Turner 2018 Perimeter Shooter 568 0.53 0.34 0.35 0.26 0.38 0.39 0.47 0.44 0.42
Al-Farouq Aminu 2018 Perimeter Wings/Defenders 568 0.46 0.53 0.46 0.32 0.29 0.00 0.00 0.43 0.20
Pat Connaughton 2018 Perimeter Shooter 399 0.54 0.25 0.27 0.42 0.34 0.67 0.50 0.32 0.34
Maurice Harkless 2018 Perimeter Shooter 282 0.57 0.32 0.55 0.30 0.58 0.67 1.00 0.50 0.21
Meyers Leonard 2018 Perimeter Shooter 87 0.55 0.50 0.67 0.57 0.30 0.25 0.50 0.60 0.75
2019
CJ McCollum 2019 Perimeter Wings/Defenders 1525 0.48 0.34 0.47 0.38 0.40 0.47 0.47 0.40 0.47
Al-Farouq Aminu 2019 Perimeter Wings/Defenders 631 0.48 0.41 0.31 0.25 0.35 0.33 0.20 0.37 0.31
Seth Curry 2019 Perimeter Shooter 547 0.46 0.41 0.57 0.44 0.43 0.41 0.50 0.34 0.43
Jake Layman 2019 Perimeter Shooter 419 0.68 0.35 0.24 0.30 0.41 0.50 0.25 0.37 0.35
Meyers Leonard 2019 Perimeter Shooter 292 0.68 0.17 0.50 0.51 0.44 0.00 0.33 0.42 0.49
Nik Stauskas 2019 Perimeter Shooter 239 0.45 0.41 0.42 0.32 0.34 0.44 0.00 0.54 0.37
2020
CJ McCollum 2020 Perimeter Wings/Defenders 1408 0.50 0.57 0.50 0.34 0.36 0.51 0.43 0.44 0.48
Carmelo Anthony 2020 Perimeter Wings/Defenders 778 0.51 0.56 0.29 0.34 0.34 0.43 0.39 0.42 0.32
Anfernee Simons 2020 Perimeter Shooter 591 0.43 0.35 0.42 0.25 0.37 0.35 0.41 0.43 0.44
Gary Trent Jr. 2020 Perimeter Shooter 483 0.43 0.43 0.49 0.38 0.41 0.31 0.38 0.48 0.42
2021
CJ McCollum 2021 Perimeter Wings/Defenders 1000 0.50 0.36 0.35 0.40 0.42 0.55 0.39 0.42 0.50
Carmelo Anthony 2021 Perimeter Wings/Defenders 836 0.39 0.45 0.48 0.43 0.33 0.46 0.46 0.43 0.38
Gary Trent Jr. 2021 Perimeter Wings/Defenders 553 0.47 0.38 0.45 0.40 0.42 0.21 0.46 0.44 0.31
Robert Covington 2021 Perimeter Wings/Defenders 528 0.42 0.38 0.24 0.44 0.40 0.50 0.25 0.33 0.30
Anfernee Simons 2021 Perimeter Shooter 417 0.35 0.53 0.53 0.39 0.42 0.67 0.33 0.44 0.31
Nassir Little 2021 Perimeter Shooter 157 0.66 0.43 0.33 0.39 0.33 0.00 0.50 0.29 0.30
a Filtered for Perimeter Players

Win Probability Added by Cluster (WPA)

WPA or Win Probability Added looks at big time or clutch plays that shift the tide of a specific game. It looks at the win probility delta of previous play to current play for a specified team. WPA is only given to the primary player on a given play. Our WPA model is calculated using the following formula:

possession_win ~ Score Differential + score value of play + Seconds Left in Game

As we can see, Superstars add a mean of 2.95% Win probability per play. What’s interesting is that Perimeter Shooters, your offensive spark off the bench, do just that and can add nearly 2% in WPA on avg. We suspect a lot of their WPA comes from clutch 3 point shots in adding to score differential. Perimeter Shooters also are likely to log a lot WPA during garbage time where they get a lot more minutes as seem their 4% WPA in the 4th quarter. Filtering this data for 750 plays helps to reduce some of the garbage time plays in a given season. Another interesting observation is the nearly 5% WPA added by Superstars in the 3rd quarter. That’s where they start to close out games and add to their stats.

Suprisingly Floor Generals can lose WPA but that may be due to their inability to provide sufficient amount of scoring.

Avg Win Probability Added by Cluster
Cluster Plays WPA WPA_q1 WPA_q2 WPA_q3 WPA_q4
Superstars 428886 0.030 0.013 0.024 0.050 0.029
Perimeter Shooter 407838 0.022 0.006 0.022 0.016 0.040
Scoring Big Man 384011 0.019 0.014 0.014 0.028 0.022
Defensive Big Man 282261 0.008 0.003 0.006 0.003 0.018
Perimeter Wings/Defenders 529119 0.004 0.003 0.005 0.005 0.003
Floor Generals 295881 -0.012 -0.010 -0.012 -0.021 -0.003
Role Player 175991 -0.016 -0.005 -0.007 -0.035 -0.018
a Filtered for plays during first 4 quarters from 2016-2021; Only looking for those w/ at least 750 plays in a season

CJ McCollum’s WPA in 2019 was the best of his career adding nearly 4.6% in Win probability per play he was primarily apart of. That provide a huge boost to the team. Since then, he’s been a detriment to Win percentage for the Blazers. We can see the argument of earlier how Championship teams have more Perimeter Shooters on the roster as they provide the necessary spark to the offense off the bench. Aminu/Crabbe in 2017, Connaughton in 2018, Curry in 2019. Regardless of the WPA in 4th quarter (likely garbage time) a lot of these players were an even spark throughout the game and provided a much needed jolt to the offense for when Dame/CJ were having an off shooting night. Such was the case for Seth Curry whose 14.3% WPA avg in 2019 was critical for the teams run to Western Conference Finals. We can see Simons is the only person currently on the roster, which makes sense for his career development. We would suggest the Blazers to target a Perimeter Shooter to provide a jolt to the secondary units.

Avg Win Probability Added by Cluster
Season Player Cluster Plays WPA WPA_q1 WPA_q2 WPA_q3 WPA_q4
2016
2016 Gerald Henderson Perimeter Shooter 1310 0.051 0.029 0.038 0.062 0.074
2016 Noah Vonleh Role Player 1053 0.042 0.017 0.073 0.055 0.041
2016 Maurice Harkless Defensive Big Man 1462 0.039 0.039 0.031 0.079 0.009
2016 Al-Farouq Aminu Perimeter Wings/Defenders 2153 0.027 0.007 0.003 0.053 0.053
2016 CJ McCollum Superstars 2881 0.025 0.025 0.029 0.014 0.033
2016 Mason Plumlee Scoring Big Man 2437 0.020 0.015 0.006 0.019 0.045
2016 Damian Lillard Superstars 3305 0.019 0.007 0.023 0.040 0.008
2016 Allen Crabbe Perimeter Shooter 1792 0.014 0.003 0.018 0.027 0.008
2016 Meyers Leonard Perimeter Shooter 1328 -0.002 -0.040 0.063 -0.016 -0.009
2017
2017 Al-Farouq Aminu Perimeter Wings/Defenders 1566 0.037 0.023 0.063 0.014 0.046
2017 Allen Crabbe Perimeter Shooter 1589 0.022 -0.009 0.042 0.038 0.010
2017 Meyers Leonard Perimeter Shooter 1099 0.009 0.028 0.023 0.000 -0.015
2017 Damian Lillard Superstars 3165 0.006 0.009 0.014 -0.007 0.010
2017 CJ McCollum Superstars 2861 0.003 0.015 -0.022 0.012 0.010
2017 Maurice Harkless Perimeter Wings/Defenders 1705 0.003 0.009 0.013 -0.015 0.007
2017 Evan Turner Floor Generals 1487 0.003 0.002 0.008 -0.023 0.025
2017 Mason Plumlee Scoring Big Man 1586 0.001 0.010 -0.023 0.038 -0.026
2017 Noah Vonleh Defensive Big Man 1282 -0.013 0.031 0.041 0.024 -0.145
2018
2018 Pat Connaughton Perimeter Shooter 1104 0.093 0.045 0.117 0.077 0.128
2018 Zach Collins Role Player 1052 0.081 0.031 0.086 0.014 0.161
2018 Maurice Harkless Perimeter Shooter 848 0.065 0.029 0.056 0.105 0.069
2018 Ed Davis Defensive Big Man 1557 0.063 0.014 0.068 0.074 0.101
2018 Evan Turner Perimeter Shooter 1489 0.059 0.029 0.073 0.070 0.066
2018 Jusuf Nurkic Scoring Big Man 2768 0.051 0.026 0.048 0.096 0.023
2018 Al-Farouq Aminu Perimeter Wings/Defenders 1706 0.046 0.025 0.049 0.071 0.034
2018 Damian Lillard Superstars 2951 0.040 0.030 0.059 0.079 -0.018
2018 CJ McCollum Perimeter Wings/Defenders 2786 0.035 0.027 0.046 0.031 0.037
2018 Shabazz Napier Floor Generals 1195 0.032 -0.021 0.041 -0.031 0.075
2019
2019 Seth Curry Perimeter Shooter 1202 0.143 0.056 0.146 0.097 0.209
2019 Jake Layman Perimeter Shooter 1134 0.108 0.089 0.068 0.150 0.122
2019 Zach Collins Defensive Big Man 1672 0.094 0.047 0.067 0.072 0.167
2019 Evan Turner Floor Generals 1537 0.079 0.038 0.056 0.091 0.123
2019 Jusuf Nurkic Scoring Big Man 2632 0.055 0.038 0.044 0.115 0.012
2019 Meyers Leonard Perimeter Shooter 1034 0.055 0.053 0.076 0.006 0.074
2019 Al-Farouq Aminu Perimeter Wings/Defenders 2087 0.053 0.028 0.048 0.088 0.041
2019 CJ McCollum Perimeter Wings/Defenders 2719 0.046 0.032 0.025 0.077 0.049
2019 Damian Lillard Superstars 3566 0.043 0.035 0.051 0.082 -0.016
2019 Maurice Harkless Defensive Big Man 1342 0.037 0.012 0.030 0.093 0.000
2020
2020 Hassan Whiteside Scoring Big Man 2527 -0.010 0.018 -0.020 -0.010 -0.033
2020 Damian Lillard Superstars 2792 -0.021 0.012 -0.030 -0.024 -0.046
2020 Gary Trent Jr. Perimeter Shooter 1010 -0.028 0.025 0.010 -0.083 -0.062
2020 Kent Bazemore Role Player 934 -0.031 0.025 0.014 -0.064 -0.112
2020 CJ McCollum Perimeter Wings/Defenders 2557 -0.032 -0.008 -0.009 -0.074 -0.040
2020 Carmelo Anthony Perimeter Wings/Defenders 1898 -0.034 0.001 -0.029 -0.062 -0.056
2020 Mario Hezonja Role Player 901 -0.039 0.020 -0.006 -0.050 -0.111
2020 Anfernee Simons Perimeter Shooter 1333 -0.073 0.028 -0.050 -0.072 -0.163
2021
2021 Anfernee Simons Perimeter Shooter 952 0.097 0.071 0.137 0.100 0.073
2021 Derrick Jones Jr. Defensive Big Man 981 0.030 0.036 0.008 0.045 0.032
2021 Carmelo Anthony Perimeter Wings/Defenders 1742 0.022 0.019 0.044 -0.002 0.018
2021 Enes Kanter Scoring Big Man 2100 0.016 -0.012 0.034 0.027 0.017
2021 Jusuf Nurkic Scoring Big Man 1306 0.007 -0.014 -0.008 0.040 0.011
2021 Damian Lillard Superstars 2802 0.002 0.014 -0.017 0.038 -0.047
2021 Robert Covington Perimeter Wings/Defenders 1671 0.002 0.015 0.001 -0.003 -0.001
2021 CJ McCollum Perimeter Wings/Defenders 1721 -0.012 0.002 -0.031 -0.036 0.022
2021 Gary Trent Jr. Perimeter Wings/Defenders 971 -0.025 0.013 0.039 -0.034 -0.112
a Filtered for plays during first 4 quarters; Only showing players w/ >750 plays for a given sesason

In looking at the top Perimeter Shooters, we can see that Anfernee Simon is the 7th highest in terms of WPA added for those with at least 750 plays in the 2020-21 season. Highlighted in grey are those with positive WPA and are available free agents. Bryn Forbes would be a cheap FA option (2020-21 salary of $2.3MM). He will likely go more than $2.3MM given he was on the Bucks but still a good spark off the bench. JaMychal Green could be another option if Forbes is taken.

Avg Win Probability Added by Perimeter Shooters
Player Cluster Plays WPA WPA_q1 WPA_q2 WPA_q3 WPA_q4
Georges Niang Perimeter Shooter 1077 0.167 0.043 0.127 0.183 0.288
Matisse Thybulle Perimeter Shooter 907 0.148 0.130 0.160 0.076 0.208
Furkan Korkmaz Perimeter Shooter 1041 0.146 0.121 0.134 0.145 0.181
PJ Dozier Perimeter Shooter 917 0.146 0.064 0.139 0.173 0.198
Bryn Forbes Perimeter Shooter 1322 0.134 0.090 0.148 0.131 0.158
Luke Kennard Perimeter Shooter 1076 0.102 0.061 0.080 0.058 0.183
Anfernee Simons Perimeter Shooter 952 0.097 0.071 0.137 0.100 0.073
Pat Connaughton Perimeter Shooter 1599 0.090 0.064 0.095 0.128 0.074
Monte Morris Perimeter Shooter 972 0.087 0.097 0.131 0.079 0.040
JaMychal Green Perimeter Shooter 1206 0.084 0.034 0.101 0.036 0.144
Nicolas Batum Perimeter Shooter 1472 0.074 0.011 0.060 0.105 0.117
Patrick Beverley Perimeter Shooter 860 0.068 0.020 0.034 0.103 0.125
Reggie Jackson Perimeter Shooter 1692 0.062 0.011 0.101 0.032 0.095
Terance Mann Perimeter Shooter 1359 0.056 0.019 0.003 0.021 0.139
Tyrese Maxey Perimeter Shooter 1029 0.056 0.025 0.052 -0.073 0.134
Maxi Kleber Perimeter Shooter 1003 0.056 0.053 0.031 0.048 0.103
Grayson Allen Perimeter Shooter 1059 0.047 0.019 0.019 0.076 0.089
Desmond Bane Perimeter Shooter 1329 0.040 0.018 -0.017 0.027 0.133
Andre Iguodala Perimeter Shooter 893 0.039 -0.015 0.000 -0.006 0.132
Tyus Jones Perimeter Shooter 938 0.038 -0.005 0.015 0.114 0.051
Kent Bazemore Perimeter Shooter 1215 0.022 -0.027 0.028 0.001 0.111
De’Anthony Melton Perimeter Shooter 1101 0.022 0.036 0.039 -0.014 0.026
Immanuel Quickley Perimeter Shooter 1305 0.016 0.013 0.068 -0.085 0.012
Kentavious Caldwell-Pope Perimeter Shooter 1222 0.016 0.039 -0.007 0.040 -0.020
Jordan Poole Perimeter Shooter 1006 0.015 -0.031 -0.002 0.133 0.007
Trey Burke Perimeter Shooter 761 0.011 -0.012 0.014 0.029 0.010
Markieff Morris Perimeter Shooter 1074 -0.003 -0.007 0.011 0.002 -0.021
Damion Lee Perimeter Shooter 805 -0.004 -0.042 -0.017 0.001 0.023
Patrick Williams Perimeter Shooter 1493 -0.007 -0.039 -0.012 0.008 0.009
Edmond Sumner Perimeter Shooter 750 -0.008 0.036 0.025 -0.069 -0.029
Payton Pritchard Perimeter Shooter 1045 -0.021 -0.018 -0.020 0.003 -0.043
Patty Mills Perimeter Shooter 1243 -0.025 -0.040 -0.025 -0.040 0.009
Garrett Temple Perimeter Shooter 922 -0.025 -0.060 -0.052 0.009 0.000
Denzel Valentine Perimeter Shooter 876 -0.030 -0.031 -0.036 -0.130 0.030
Eric Paschall Perimeter Shooter 754 -0.034 -0.038 -0.034 -0.135 0.004
Grant Williams Perimeter Shooter 944 -0.037 -0.036 -0.098 -0.083 0.040
Wesley Matthews Perimeter Shooter 763 -0.049 -0.087 -0.051 -0.095 0.045
Devin Vassell Perimeter Shooter 887 -0.078 -0.091 -0.057 -0.096 -0.069
Sterling Brown Perimeter Shooter 867 -0.081 -0.012 -0.041 -0.130 -0.138
Chuma Okeke Perimeter Shooter 814 -0.091 -0.033 -0.044 -0.096 -0.189
Kenrich Williams Perimeter Shooter 1159 -0.121 -0.006 -0.104 -0.176 -0.176
Jaden McDaniels Perimeter Shooter 1040 -0.122 -0.076 -0.134 -0.126 -0.154
Dean Wade Perimeter Shooter 879 -0.122 -0.080 -0.097 -0.105 -0.191
a Filtered for plays during first 4 quarters; Only showing players w/ >750 plays for a given sesason

Value of Clusters

Not surprisingly, Superstars are valued the highest but have the highest market inefficients in terms of salary (given high standard deviation). This could be due to not all players being paid out yet for their superstar performance. What’s interesting is the average values of a Scoring Big Man is $10MM less per year. Another interesting trend is how over values “Floor Generals” are in the NBA given their low VORP avg. in 2020/21 season. This could be due to their ability to orchestrate the offense but still maybe not worth the cost.

Value of Player Cluster
Cluster VORP AVG VORP STDV 2020-21 AVG 2020-21 STDV
Superstar 2.60 1.55 25527240 11753101
Scoring Big Man 2.24 1.18 15670392 9989600
Perimeter Wing/Defender 0.77 0.79 9757010 7515574
Defensive Big Man 0.35 0.52 4948332 4660940
Perimeter Shooter 0.13 0.41 3908048 3338896
Floor General 0.08 0.75 8148999 6204521
Role Player -0.36 0.33 2458514 1511230
CJ McCollum & Derek Jones Jr contract hurt for the Blazers. CJ McCollum is about 3x the value of Perimeter Wing/Defender contract and Derrick Jones is nearly 2x that of a normal defensive big. Norman Powell (not listed because he only played 27 games with the Blazers and threshold below for 30 games) had a VORP of 0.1, which isn’t an ideal FA target. Norman Powell’s 2020-21 salary was ~$10.5M. Enes Kanter’s value is 2x cheaper than a Scoring Big Man.
2021 Clusters & Values of Portland
player pos age yr tm mp pts vorp cluster 2020-21 2021-22 Guaranteed
Damian Lillard PG 30 2021 POR 35.8 28.8 4.8 Superstar $31,626,953 $43,750,000 $227,626,953
CJ McCollum SG 29 2021 POR 34.0 23.1 2.1 Perimeter Wing/Defender $29,354,152 $30,864,198 $129,354,152
Robert Covington PF 30 2021 POR 32.0 8.5 1.0 Perimeter Wing/Defender $12,138,345 $12,975,471 $25,113,816
Enes Kanter C 28 2021 POR 24.4 11.2 1.0 Scoring Big Man $5,005,350 $5,005,350
Jusuf Nurkic C 26 2021 POR 23.8 11.5 0.9 Scoring Big Man $12,000,000 $12,000,000 $16,000,000
Carmelo Anthony PF 36 2021 POR 24.5 13.4 0.2 Perimeter Wing/Defender $2,564,753 $2,564,753
Anfernee Simons SG 21 2021 POR 17.3 7.8 0.2 Perimeter Shooter $2,252,040 $3,938,818 $6,190,858
Derrick Jones Jr. SF 23 2021 POR 22.7 6.8 0.1 Defensive Big Man $9,268,293 $9,731,707 $19,000,000
Harry Giles C 22 2021 POR 9.2 2.8 -0.1 Defensive Big Man $1,678,854 $1,678,854
CJ Elleby SF 20 2021 POR 6.4 2.3 -0.2 Role Player $898,310 $1,517,981 $2,416,291
Nassir Little PF 20 2021 POR 13.3 4.6 -0.2 Perimeter Shooter $2,210,640 $2,316,240 $4,526,880

2020-21 Free Agent Targets

In terms of possible FA targets, the Blazers need a likely Scoring Big Man (if they can’t resign Kanter), a Perimeter Wing/Defender and/or Shooter. We’d opt for a Shooter to add some depth to the roster but getting a younger Perimeter Wing/Defender may be best to backup Carmelo Anthony and Robert Covington who are both 30+. In looking at the available FA list, we’ve identified a few targets for the Blazers. The options are the following:

  1. If the Blazers, can’t resign Enes Kanter, The Blazers should sign Richaun Holmes. He’s the same price as Kanter, a bit more durable in terms of MP/G and a year younger.

  2. Sign and Trade for Lauri Markkanen. Might be worth to move Derrick Jones Jr. for Lauri Markkanen who is young and could be the future wing for the roster. Lauri is similar price to Derrick Jones and likely an odd man out in Chicago. Derrick Jones is a better fit to move into the Chicago rotation.

  3. Duncan Robinson could be a good off the bench for the Blazers if the Heat don’t put out a viable offer.

  4. Cheap bench signings would Bryn Forbes that could be good offensive shooters off the bench.

2021/22 NBA Free Agents
player pos age yr tm mp pts vorp cluster 2020-21 type rights
Kawhi Leonard SF 29 2021 LAC 34.1 24.8 3.9 Superstar $34,379,100 PO
DeMar DeRozan PF 31 2021 SAS 33.7 21.6 2.7 Superstar $27,739,975 UFA Bird
John Collins PF 23 2021 ATL 29.3 17.6 1.9 Scoring Big Man $4,137,302 RFA Bird
Montrezl Harrell C 27 2021 LAL 22.9 13.5 1.9 Scoring Big Man $9,258,000 PO
Danny Green SF 33 2021 PHI 28.0 9.5 1.7 Perimeter Wing/Defender $15,365,854 UFA Early Bird
Lonzo Ball PG 23 2021 NOP 31.8 14.6 1.6 Perimeter Wing/Defender $11,003,782 RFA Bird
Nicolas Batum SF 32 2021 LAC 27.4 8.1 1.6 Perimeter Shooter $11,608,231 UFA Non-Bird
T.J. McConnell PG 28 2021 IND 26.0 8.6 1.6 Floor General $3,500,000 UFA Early Bird
Kyle Lowry PG 34 2021 TOR 34.8 17.2 1.3 Superstar $30,000,000 UFA Bird
Nerlens Noel C 26 2021 NYK 24.2 5.1 1.2 Defensive Big Man $5,000,000 UFA Non-Bird
Bobby Portis C 25 2021 MIL 20.8 11.4 1.2 Defensive Big Man $3,623,000 PO
Jarrett Allen C 22 2021 CLE 30.3 13.2 1.1 Scoring Big Man $3,909,902 RFA Bird
Tim Hardaway Jr. SG 28 2021 DAL 28.4 16.6 1.1 Perimeter Wing/Defender $18,975,000 UFA Bird
Richaun Holmes C 27 2021 SAC 29.2 14.2 1.0 Scoring Big Man $5,005,350 UFA Early Bird
Enes Kanter C 28 2021 POR 24.4 11.2 1.0 Scoring Big Man $5,005,350 UFA Early Bird
Reggie Bullock SF 29 2021 NYK 30.0 10.9 0.9 Perimeter Wing/Defender $4,200,000 UFA Early Bird
Alec Burks SG 29 2021 NYK 25.6 12.7 0.9 Perimeter Wing/Defender $6,000,000 UFA Non-Bird
Derrick Rose PG 32 2021 NYK 26.8 14.9 0.9 Perimeter Wing/Defender $7,682,927 UFA Early Bird
Taj Gibson PF 35 2021 NYK 20.8 5.4 0.8 Defensive Big Man $3,283,684 UFA Non-Bird
Reggie Jackson SG 30 2021 LAC 23.0 10.7 0.8 Perimeter Shooter $2,331,593 UFA Early Bird
Serge Ibaka C 31 2021 LAC 23.3 11.1 0.7 Defensive Big Man $9,258,000 PO
Lauri Markkanen PF 23 2021 CHI 25.8 13.6 0.7 Perimeter Wing/Defender $6,731,508 RFA Bird
Paul Millsap PF 35 2021 DEN 20.8 9.0 0.7 Defensive Big Man $10,000,000 UFA Bird
Alex Caruso PG 26 2021 LAL 21.0 6.4 0.6 Floor General $2,750,000 UFA Bird
Doug McDermott PF 29 2021 IND 24.5 13.6 0.6 Perimeter Wing/Defender $7,333,333 UFA Bird
Kendrick Nunn PG 25 2021 MIA 29.5 14.6 0.6 Perimeter Wing/Defender $1,663,861 RFA Bird
Duncan Robinson SF 26 2021 MIA 31.4 13.1 0.5 Perimeter Wing/Defender $1,663,861 RFA Bird
Wayne Ellington SG 33 2021 DET 22.0 9.6 0.4 Perimeter Shooter $3,005,225 UFA Non-Bird
Willy Hernangomez C 26 2021 NOP 18.0 7.8 0.4 Defensive Big Man $1,727,145 UFA Non-Bird
Andre Iguodala SF 37 2021 MIA 21.3 4.4 0.4 Perimeter Shooter $15,000,000 CO
Alex Len C 27 2021 WAS 15.8 7.1 0.4 Defensive Big Man $4,032,648 UFA Non-Bird
Raul Neto PG 28 2021 WAS 21.9 8.7 0.4 Perimeter Shooter $1,882,867 UFA Non-Bird
Dennis Schroder SG 27 2021 LAL 32.1 15.4 0.4 Floor General $15,500,000 UFA Bird
Jarred Vanderbilt PF 21 2021 MIN 17.8 5.4 0.4 Defensive Big Man $1,663,861 RFA Bird
Josh Hart SF 25 2021 NOP 28.7 9.2 0.3 Perimeter Wing/Defender $3,491,159 RFA Bird
Talen Horton-Tucker SG 20 2021 LAL 20.1 9.0 0.3 Floor General $1,517,981 RFA Early Bird
Robin Lopez C 32 2021 WAS 19.1 9.0 0.3 Defensive Big Man $7,300,000 UFA Non-Bird
David Nwaba SF 28 2021 HOU 22.6 9.2 0.3 Defensive Big Man $1,862,250 UFA Early Bird
Tony Snell SG 29 2021 ATL 21.1 5.3 0.3 Perimeter Shooter $12,178,571 UFA Bird
Carmelo Anthony PF 36 2021 POR 24.5 13.4 0.2 Perimeter Wing/Defender $2,564,753 UFA Early Bird
Trevor Ariza SF 35 2021 MIA 28.0 9.4 0.2 Perimeter Wing/Defender $12,800,000 UFA Early Bird
Bryn Forbes SG 27 2021 MIL 19.3 10.0 0.2 Perimeter Shooter $2,337,145 PO
Skylar Mays SG 23 2021 ATL 8.2 3.8 0.2 Perimeter Shooter NA RFA Non-Bird
Patrick Patterson PF 31 2021 LAC 15.3 5.2 0.2 Perimeter Shooter $3,814,768 UFA Early Bird
Kent Bazemore SF 31 2021 GSW 19.9 7.2 0.1 Perimeter Shooter $2,320,044 UFA Non-Bird
Sterling Brown SG 25 2021 HOU 24.1 8.2 0.1 Perimeter Shooter $1,678,854 UFA Non-Bird
Willie Cauley-Stein C 27 2021 DAL 17.1 5.3 0.1 Defensive Big Man $4,000,000 CO
Derrick Jones Jr. SF 23 2021 POR 22.7 6.8 0.1 Defensive Big Man $9,268,293 PO
Boban Marjanovic C 32 2021 DAL 8.2 4.7 0.1 Defensive Big Man $3,500,000 UFA Early Bird
Will Barton SF 30 2021 DEN 31.0 12.7 0.0 Perimeter Wing/Defender $13,920,000 UFA Bird
Keita Bates-Diop SF 25 2021 SAS 8.2 2.6 0.0 Role Player NA RFA Non-Bird
JaMychal Green PF 30 2021 DEN 19.3 8.1 0.0 Perimeter Shooter $7,199,760 PO
Dwight Howard C 35 2021 PHI 17.3 7.0 0.0 Defensive Big Man $2,564,753 UFA Non-Bird
Frank Jackson PG 22 2021 DET 18.5 9.8 0.0 Perimeter Shooter NA UFA Non-Bird
Saben Lee PG 21 2021 DET 16.3 5.6 0.0 Floor General NA RFA Non-Bird
Jordan McLaughlin PG 24 2021 MIN 18.4 5.0 0.0 Role Player NA RFA Early Bird
Frank Ntilikina PG 22 2021 NYK 9.8 2.7 0.0 Role Player $6,176,578 RFA Bird
Josh Richardson SG 27 2021 DAL 30.3 12.1 0.0 Perimeter Wing/Defender $10,800,000 PO
Max Strus SF 24 2021 MIA 13.0 6.1 0.0 Perimeter Shooter NA RFA Non-Bird
Ryan Arcidiacono PG 26 2021 CHI 10.2 3.1 -0.1 Perimeter Shooter $3,000,000 CO
Amir Coffey SG 23 2021 LAC 9.0 3.2 -0.1 Perimeter Shooter NA RFA Early Bird
Harry Giles C 22 2021 POR 9.2 2.8 -0.1 Defensive Big Man $1,678,854 UFA Non-Bird
Stanley Johnson PF 24 2021 TOR 16.5 4.4 -0.1 Role Player $3,801,000 UFA Early Bird
Nathan Knight PF 23 2021 ATL 8.5 3.8 -0.1 Role Player NA RFA Non-Bird
Garrison Mathews SG 24 2021 WAS 16.2 5.5 -0.1 Perimeter Shooter NA RFA Early Bird
Wesley Matthews SG 34 2021 LAL 19.5 4.8 -0.1 Perimeter Shooter $3,623,000 UFA Non-Bird
Kelly Oubre Jr. SF 25 2021 GSW 30.7 15.4 -0.1 Perimeter Wing/Defender $14,375,000 UFA Bird
Hassan Whiteside C 31 2021 SAC 15.2 8.1 -0.1 Defensive Big Man $2,320,044 UFA Non-Bird
Brandon Goodwin PG 25 2021 ATL 13.2 4.9 -0.2 Role Player $1,701,593 RFA Early Bird
Nico Mannion PG 19 2021 GSW 12.1 4.1 -0.2 Role Player NA RFA Non-Bird
Semi Ojeleye PF 26 2021 BOS 17.0 4.6 -0.2 Perimeter Shooter $1,752,950 UFA Bird
Mike Scott PF 32 2021 PHI 16.7 4.2 -0.2 Role Player $5,005,350 UFA Early Bird
Edmond Sumner SG 25 2021 IND 16.2 7.5 -0.2 Perimeter Shooter $2,160,000 CO
Thanasis Antetokounmpo SF 28 2021 MIL 9.7 2.9 -0.3 Role Player $1,701,593 RFA Early Bird
Goran Dragic PG 34 2021 MIA 26.7 13.4 -0.3 Floor General $18,000,000 CO
Kyle Guy PG 23 2021 SAC 7.6 2.8 -0.3 Role Player NA RFA Early Bird
Solomon Hill PF 29 2021 ATL 21.3 4.5 -0.3 Role Player $2,174,318 UFA Non-Bird
Markieff Morris PF 31 2021 LAL 19.7 6.7 -0.3 Perimeter Shooter $2,331,593 UFA Early Bird
Sviatoslav Mykhailiuk SG 23 2021 OKC 23.0 10.3 -0.3 Perimeter Shooter $1,663,861 RFA Bird
Denzel Valentine SG 27 2021 CHI 16.7 6.5 -0.3 Perimeter Shooter $4,642,800 UFA Bird
Markus Howard SG 21 2021 DEN 5.5 2.8 -0.4 Role Player NA RFA Non-Bird
Isaac Bonga SF 21 2021 WAS 10.8 2.0 -0.5 Role Player $1,663,861 RFA Bird
Elfrid Payton PG 26 2021 NYK 23.6 10.1 -0.5 Floor General $5,760,000 UFA Non-Bird
Garrett Temple SG 34 2021 CHI 27.3 7.6 -0.6 Perimeter Shooter $4,767,000 UFA Non-Bird
Gabe Vincent PG 24 2021 MIA 13.1 4.8 -0.6 Role Player NA RFA Early Bird
Chasson Randle PG 27 2021 ORL 20.4 6.5 -0.9 Role Player NA UFA Non-Bird
a NA for salary likely means data couldn’t be found
This would be hypothetical what the Blazers look like with their FA signings.
2021/22 Portland Trail Blazers
player pos age yr tm mp pts vorp cluster 2020-21
Damian Lillard PG 30 2021 POR 35.8 28.8 4.8 Superstar $31,626,953
CJ McCollum SG 29 2021 POR 34.0 23.1 2.1 Perimeter Wing/Defender $29,354,152
Robert Covington PF 30 2021 POR 32.0 8.5 1.0 Perimeter Wing/Defender $12,138,345
Richaun Holmes C 27 2021 SAC 29.2 14.2 1.0 Scoring Big Man $5,005,350
Enes Kanter C 28 2021 POR 24.4 11.2 1.0 Scoring Big Man $5,005,350
Jusuf Nurkic C 26 2021 POR 23.8 11.5 0.9 Scoring Big Man $12,000,000
Lauri Markkanen PF 23 2021 CHI 25.8 13.6 0.7 Perimeter Wing/Defender $6,731,508
Duncan Robinson SF 26 2021 MIA 31.4 13.1 0.5 Perimeter Wing/Defender $1,663,861
Bryn Forbes SG 27 2021 MIL 19.3 10.0 0.2 Perimeter Shooter $2,337,145
Anfernee Simons SG 21 2021 POR 17.3 7.8 0.2 Perimeter Shooter $2,252,040
Derrick Jones Jr. SF 23 2021 POR 22.7 6.8 0.1 Defensive Big Man $9,268,293
CJ Elleby SF 20 2021 POR 6.4 2.3 -0.2 Role Player $898,310

Superstar Trade Targets

Below are the the players who played in the Superstar range for the 2020-21 season. We can see it is an elite 42 players in the league. In terms of trade targets for the Blazers, the Pascal Siakam makes the most sense to pair Dame with a “true” superstar and have someone with a comparable salary to CJ McCollum at $30MM. A Jaylen Brown could be another nice addition and be a $7MM saving for Boston if swapped with CJ. These two targets are younger than CJ still playing at elite levels.

2021 NBA Superstar Cluster
player pos age yr tm mp pts vorp cluster 2020-21
Nikola Jokic C 25 2021 DEN 34.6 26.4 8.6 Superstar $28,542,009
Stephen Curry PG 32 2021 GSW 34.2 32.0 5.5 Superstar $43,006,362
Luka Doncic PG 21 2021 DAL 34.3 27.7 5.0 Superstar $8,049,360
Damian Lillard PG 30 2021 POR 35.8 28.8 4.8 Superstar $31,626,953
Jimmy Butler SF 31 2021 MIA 33.6 21.5 4.2 Superstar $34,379,100
Kawhi Leonard SF 29 2021 LAC 34.1 24.8 3.9 Superstar $34,379,100
Julius Randle PF 26 2021 NYK 37.6 24.1 3.8 Superstar $18,900,000
Chris Paul PG 35 2021 PHO 31.4 16.4 3.7 Superstar $41,358,814
LeBron James PG 36 2021 LAL 33.4 25.0 3.6 Superstar $39,219,565
Kyrie Irving PG 28 2021 BRK 34.9 26.9 3.5 Superstar $33,329,100
Jayson Tatum SF 22 2021 BOS 35.8 26.4 3.3 Superstar $9,897,120
Russell Westbrook PG 32 2021 WAS 36.4 22.2 3.2 Superstar $41,358,814
James Harden PG 31 2021 BRK 36.6 24.6 3.0 Superstar $40,824,000
Trae Young PG 22 2021 ATL 33.7 25.3 3.0 Superstar $6,571,800
Zach LaVine SG 25 2021 CHI 35.1 27.4 2.9 Superstar $19,500,000
Bradley Beal SG 27 2021 WAS 35.8 31.3 2.8 Superstar $28,751,775
DeMar DeRozan PF 31 2021 SAS 33.7 21.6 2.7 Superstar $27,739,975
Tobias Harris PF 28 2021 PHI 32.5 19.5 2.7 Superstar $33,517,241
Kevin Durant PF 32 2021 BRK 33.1 26.9 2.6 Superstar $39,058,950
Paul George SF 30 2021 LAC 33.7 23.3 2.6 Superstar $35,450,412
Jrue Holiday PG 30 2021 MIL 32.3 17.7 2.6 Superstar $26,131,111
Donovan Mitchell PG 24 2021 UTA 33.4 26.4 2.5 Superstar $5,195,501
Mike Conley PG 33 2021 UTA 29.4 16.2 2.4 Superstar $34,504,132
Jaylen Brown SG 24 2021 BOS 34.5 24.7 2.3 Superstar $22,991,071
Brandon Ingram SF 23 2021 NOP 34.3 23.8 2.2 Superstar $27,285,000
Fred VanVleet SG 26 2021 TOR 36.5 19.6 2.0 Superstar $21,250,000
Khris Middleton SF 29 2021 MIL 33.4 20.4 1.9 Superstar $33,051,724
Malcolm Brogdon PG 28 2021 IND 34.5 21.2 1.7 Superstar $20,700,000
De’Aaron Fox PG 23 2021 SAC 35.1 25.2 1.7 Superstar $8,099,627
Shai Gilgeous-Alexander SG 22 2021 OKC 33.7 23.7 1.7 Superstar $4,141,320
Jamal Murray PG 23 2021 DEN 35.5 21.2 1.6 Superstar $29,250,000
LaMelo Ball PG 19 2021 CHO 28.8 15.7 1.4 Superstar $7,839,960
Jerami Grant SF 26 2021 DET 33.9 22.3 1.3 Superstar $19,047,619
Gordon Hayward SF 30 2021 CHO 34.0 19.6 1.3 Superstar $28,500,000
Kyle Lowry PG 34 2021 TOR 34.8 17.2 1.3 Superstar $30,000,000
Pascal Siakam PF 26 2021 TOR 35.8 21.4 1.2 Superstar $29,000,000
Devin Booker SG 24 2021 PHO 33.9 25.6 1.1 Superstar $29,430,000
D’Angelo Russell PG 24 2021 MIN 28.5 19.0 1.0 Superstar $28,649,250
Collin Sexton SG 22 2021 CLE 35.3 24.3 1.0 Superstar $4,991,880
Ja Morant PG 21 2021 MEM 32.6 19.1 0.6 Superstar $9,166,800
John Wall PG 30 2021 HOU 32.2 20.6 0.6 Superstar $41,254,920
Caris LeVert SG 26 2021 IND 32.9 20.7 0.5 Superstar $16,203,704

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